# Using convolutional neural networks to count parrot nest‐entrances on photographs from the largest known colony of Psittaciformes

**Authors:** Gabriel L. Zanellato, Gabriel A. Pagnossin, Mauricio Failla, Juan F. Masello

PMC · DOI: 10.1002/ece3.70172 · 2024-08-13

## TL;DR

This study uses AI to count parrot nests in the world's largest parrot colony, showing how human activity has changed their nesting patterns.

## Contribution

Applying CNNs to count parrot nest entrances and detect human-induced distribution changes in a large Psittaciformes colony.

## Key findings

- U-Net CNN achieved the best performance with a mean absolute error of 2.7 nest-entrances.
- Nest-entrance distribution has changed significantly due to human-induced disturbance over 20 years.
- The El Cóndor colony hosts 71% of the global Burrowing Parrot population, making it critical for species conservation.

## Abstract

Counting animal populations is fundamental to understand ecological processes. Counts make it possible to estimate the size of an animal population at specific points in time, which is essential information for understanding demographic change. However, in the case of large populations, counts are time‐consuming, particularly if carried out manually. Here, we took advantage of convolutional neural networks (CNN) to count the total number of nest‐entrances in 222 photographs covering the largest known Psittaciformes (Aves) colony in the world. We conducted our study at the largest Burrowing Parrot Cyanoliseus patagonus colony, located on a cliff facing the Atlantic Ocean in the vicinity of El Cóndor village, in north‐eastern Patagonia, Argentina. We also aimed to investigate the distribution of nest‐entrances along the cliff with the colony. For this, we used three CNN architectures, U‐Net, ResUnet, and DeepLabv3. The U‐Net architecture showed the best performance, counting a mean of 59,842 Burrowing Parrot nest‐entrances across the colony, with a mean absolute error of 2.7 nest‐entrances over the testing patches, measured as the difference between actual and predicted counts per patch. Compared to a previous study conducted at El Cóndor colony more than 20 years ago, the CNN architectures also detected noteworthy differences in the distribution of the nest‐entrances along the cliff. We show that the strong changes observed in the distribution of nest‐entrances are a measurable effect of a long record of human‐induced disturbance to the Burrowing Parrot colony at El Cóndor. Given the paramount importance of the Burrowing Parrot colony at El Cóndor, which concentrates 71% of the world's population of this species, we advocate that it is imperative to reduce such a degree of disturbance before the parrots reach the limit of their capacity of adaptation.

We used a convolutional neural network computer vision technique to count the number of nest‐entrances at the El Cóndor Burrowing Parrot colony. El Cóndor colony is of utmost importance for the conservation of the species: 71% of the global population of burrowing parrots breeds there. Any threats affecting the El Cóndor colony could utterly impact the whole of the species. This colony is also deemed the largest known Psittaciformes colony in the world. In our study, we detected noteworthy differences in the distribution of the nest‐entrances, and showed that this is a measurable effect of human‐induced disturbance.

## Linked entities

- **Species:** Cyanoliseus patagonus (taxon 309862), Psittaciformes (taxon 9223), Aves (taxon 8782)

## Full-text entities

- **Species:** Psittacidae (parrot, family) [taxon 9224], Homo sapiens (human, species) [taxon 9606], Psittaciformes (parrots and others, order) [taxon 9223], Cyanoliseus patagonus (burrowing parakeet, species) [taxon 309862]

## Figures

7 figures with captions in the complete paper: https://tomesphere.com/paper/PMC11319764/full.md

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Source: https://tomesphere.com/paper/PMC11319764